Matches in SemOpenAlex for { <https://semopenalex.org/work/W2073990167> ?p ?o ?g. }
- W2073990167 abstract "The challenge of finding small targets in big images lies in the characterization of the background clutter. Themore homogeneous the background, the more distinguishable a typical target will be from its background. Oneway to homogenize the background is to segment the image into distinct regions, each of which is individuallyhomogeneous, and then to treat each region separately. In this paper we will report on experiments in which thetarget is unspecified (it is an anomaly), and various segmentation strategies are employed, including an adaptivehierarchical tree-based scheme. We find that segmentations that employ overlap achieve better performance inthe low false alarm rate regime." @default.
- W2073990167 created "2016-06-24" @default.
- W2073990167 creator A5039687135 @default.
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- W2073990167 date "2011-05-13" @default.
- W2073990167 modified "2023-09-23" @default.
- W2073990167 title "Overlapping image segmentation for context-dependent anomaly detection" @default.
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- W2073990167 doi "https://doi.org/10.1117/12.883326" @default.
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